Instructions to use TimKond/diffusion-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TimKond/diffusion-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="TimKond/diffusion-detection") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("TimKond/diffusion-detection") model = AutoModelForImageClassification.from_pretrained("TimKond/diffusion-detection") - Notebooks
- Google Colab
- Kaggle
initial commit
Browse files- training_args.bin +1 -1
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 3887
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:be8111d37711672abda6e625db4e546a72df20e34a5202612241de16cbfe4135
|
| 3 |
size 3887
|